Your people already have the answers. They are buried in SharePoint, in a shared drive, in a database nobody queries, in four hundred PDFs. I build the system that finds them and answers in plain language, with the source attached.

An assistant your team can ask questions in normal language

Ingestion pipelines for your documents, pages and lists, kept in sync

Hybrid search over a real vector index, not one prompt stuffed with text

Answers with citations back to the source, so people can check the work

Permission trimming, so nobody sees a document they could not open themselves

I audit what you actually have first: formats, volume, and how messy it really is

I build ingestion before retrieval, because the index is only as good as what goes into it

I test against real questions your team wrote, not questions I invented

We measure, tune retrieval, then ship

Azure AI Search, Azure SQL, Microsoft Foundry, Azure OpenAI, SharePoint Graph API, Python. I have shipped this exact architecture for an enterprise client whose content sat across SharePoint documents and lists, including the unglamorous parts: ingestion, indexing, and a separate SQL path for questions that need counting rather than reading.

A sample of the real documents, one person who knows the content, and twenty questions your team wishes they could just ask out loud.

People in your company keep asking each other things a document already answers.